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Record W2133283170 · doi:10.5539/jel.v2n2p96

Write to Read in Two Different Practices: Literacy versus Technology in Focus

2013· article· en· W2133283170 on OpenAlex
Ulla Damber

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education and Learning · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyMathematics educationPedagogyInformation literacyFocus (optics)PsychologyComputer science

Abstract

fetched live from OpenAlex

Literacy acquisition by using computers and computer tablets is rapidly gaining ground in Swedish classrooms.This article explores the hypothesis that computer-writing vitalizes the learning of literacy, in comparison withapproaches using books and pencils. The results of two separate studies in two different settings whereprewriting and writing were used to enhance literacy development will be described and discussed. The results ofa recent study of classrooms where computers were used will be compared with an older study where studentsused pencils and paper for writing. The results indicated that the nature of the literacy practice was stronglylinked to the teacher’s conceptions of literacy and learning. The teachers’ choices of computers or pencils astools for writing do, however, not seem to influence the processes of writing in the classrooms. How writing wasenacted in the classrooms and the potential to further development of the literacy practices, were linked toteacher knowledge and the teacher’s conception of literacy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.429
Teacher spread0.399 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it